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Article

Pedestrian Dead Reckoning Based on Motion Mode Recognition Using a Smartphone

by 1, 1,*, 2,3, 2,3 and 2,3
1
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2
State Key Laboratory of Satellite Navigation System and Equipment Technology, Shijiazhuang 050081, China
3
The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang 050081, China
*
Author to whom correspondence should be addressed.
Received: 10 April 2018 / Revised: 27 May 2018 / Accepted: 1 June 2018 / Published: 4 June 2018
(This article belongs to the Special Issue Sensor Fusion and Novel Technologies in Positioning and Navigation)
This paper presents a pedestrian dead reckoning (PDR) approach based on motion mode recognition using a smartphone. The motion mode consists of pedestrian movement state and phone pose. With the support vector machine (SVM) and the decision tree (DT), the arbitrary combinations of movement state and phone pose can be recognized successfully. In the traditional principal component analysis based (PCA-based) method, the obtained horizontal accelerations in one stride time interval cannot be guaranteed to be horizontal and the pedestrian’s direction vector will be influenced. To solve this problem, we propose a PCA-based method with global accelerations (PCA-GA) to infer pedestrian’s headings. Besides, based on the further analysis of phone poses, an ambiguity elimination method is also developed to calibrate the obtained headings. The results indicate that the recognition accuracy of the combinations of movement states and phone poses can be 92.4%. The 50% and 75% absolute estimation errors of pedestrian’s headings are 5.6° and 9.2°, respectively. This novel PCA-GA based method can achieve higher accuracy than traditional PCA-based method and heading offset method. The localization error can reduce to around 3.5 m in a trajectory of 164 m for different movement states and phone poses. View Full-Text
Keywords: indoor localization; motion mode recognition; pedestrian dead reckoning; heading determination; smartphone sensors indoor localization; motion mode recognition; pedestrian dead reckoning; heading determination; smartphone sensors
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MDPI and ACS Style

Wang, B.; Liu, X.; Yu, B.; Jia, R.; Gan, X. Pedestrian Dead Reckoning Based on Motion Mode Recognition Using a Smartphone. Sensors 2018, 18, 1811. https://0-doi-org.brum.beds.ac.uk/10.3390/s18061811

AMA Style

Wang B, Liu X, Yu B, Jia R, Gan X. Pedestrian Dead Reckoning Based on Motion Mode Recognition Using a Smartphone. Sensors. 2018; 18(6):1811. https://0-doi-org.brum.beds.ac.uk/10.3390/s18061811

Chicago/Turabian Style

Wang, Boyuan, Xuelin Liu, Baoguo Yu, Ruicai Jia, and Xingli Gan. 2018. "Pedestrian Dead Reckoning Based on Motion Mode Recognition Using a Smartphone" Sensors 18, no. 6: 1811. https://0-doi-org.brum.beds.ac.uk/10.3390/s18061811

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